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Robust Confidence Intervals for PM2.5 Concentration Measurements in the Ecuadorian Park La Carolina [PDF]

open access: goldSensors, 2020
In this article, robust confidence intervals for PM2.5 (particles with size less than or equal to 2.5   μ m ) concentration measurements performed in La Carolina Park, Quito, Ecuador, have been built.
Wilmar Hernandez   +3 more
doaj   +4 more sources

Confidence intervals for robust estimates of measurement uncertainty [PDF]

open access: hybridAccreditation and Quality Assurance, 2020
Uncertainties arising at different stages of a measurement process can be estimated using Analysis of Variance (ANOVA) on duplicated measurements. In some cases it is also desirable to calculate confidence intervals for these uncertainties.
Fearn, Tom   +2 more
core   +8 more sources

A robust and efficient algorithm to find profile likelihood confidence intervals [PDF]

open access: hybridStat Comput 31, 38 (2021), 2020
Profile likelihood confidence intervals are a robust alternative to Wald's method if the asymptotic properties of the maximum likelihood estimator are not met. However, the constrained optimization problem defining profile likelihood confidence intervals can be difficult to solve in these situations, because the likelihood function may exhibit ...
Samuel Fischer, Mark A. Lewis
arxiv   +9 more sources

Robust Empirical Bayes Confidence Intervals [PDF]

open access: greenEconometrica, 2020
We construct robust empirical Bayes confidence intervals (EBCIs) in a normal means problem. The intervals are centered at the usual linear empirical Bayes estimator, but use a critical value accounting for shrinkage. Parametric EBCIs that assume a normal
Timothy B. Armstrong   +2 more
semanticscholar   +5 more sources

Bootstrapping Confidence Intervals For Robust Measures Of Association [PDF]

open access: bronzeJournal of Modern Applied Statistical Methods, 2003
A Monte Carlo simulation study compared four bootstrapping procedures in generating confidence intervals for the robust Winsorized and percentage bend correlations.
King, Jason E.
core   +5 more sources

Robust Confidence Intervals for the Population Mean Alternatives to the Student-t Confidence Interval

open access: goldJournal of Modern Applied Statistical Methods, 2020
In this paper, three robust confidence intervals are proposed as alternatives to the Student t confidence interval. The performance of these intervals was compared through a simulation study shows that Qn-t confidence interval performs the best and it is
Jennifer E. V. Lloyd   +8 more
semanticscholar   +6 more sources

Huber-Robust Confidence Sequences [PDF]

open access: yesarXiv, 2023
Confidence sequences are confidence intervals that can be sequentially tracked, and are valid at arbitrary data-dependent stopping times. This paper presents confidence sequences for a univariate mean of an unknown distribution with a known upper bound on the $p$-th central moment ($p$ > 1), but allowing for (at most) $\epsilon$ fraction of arbitrary ...
Ramdas, Aaditya, Wang, Hongjian
arxiv   +5 more sources

Globally Robust Confidence Intervals for Location

open access: bronzeDhaka University Journal of Science, 2012
Classical inference considers sampling variability to be the only source of uncertainty, and does not address the issue of bias caused by contamination.
M. Ershadul Haque, Jafar A Khan
semanticscholar   +5 more sources

Robust statistics, hypothesis testing, and confidence intervals for persistent homology on metric measure spaces [PDF]

open access: greenarXiv, 2012
We study distributions of persistent homology barcodes associated to taking subsamples of a fixed size from metric measure spaces. We show that such distributions provide robust invariants of metric measure spaces, and illustrate their use in hypothesis testing and providing confidence intervals for topological data analysis.
Andrew J. Blumberg   +3 more
arxiv   +4 more sources

Adaptive Robust Confidence Intervals [PDF]

open access: greenarXiv
This paper studies the construction of adaptive confidence intervals under Huber's contamination model when the contamination proportion is unknown. For the robust confidence interval of a Gaussian mean, we show that the optimal length of an adaptive interval must be exponentially wider than that of a non-adaptive one.
Yuetian Luo, Chao Gao
arxiv   +5 more sources

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